The cost of medical care is increasingly getting out of control due to a fragmentation of medical care brought about, in large part, by a proliferation of (expensive) medical tools and specialties. Furthermore each specialty is, more often than not, an outgrowth of an isolated technological solution (instrument or procedure.) A good beginning would be to change the focus of technology. This is in fact already happening.
Prior art and emerging trends are illustrated in the following articles. Note the increasing popularity of (frequency) spectrum analysis.
J. D. Andrade, "Improved Delivery and Reduced Costs Of Health Care Through Engineering: Discussion Meeting--Apr. 23-24, 1992, Washington, D.C.," IEEE Engineering in Medicine and Biology, pp. 38-41, June 1993. According to this autor cost savings could be provided by better information handling and record keeping, and by increasing the bedside or near bedside availability of tests and related information. Information and communications technologies and systems should be available to provide on-site information at the decision point. This information, together with available clinical practice guidelines and codification of diagnostic and therapeutic strategies, would permit more rapid and more effective on-site diagnosis. More effective and more remote noninvasive monitoring should be considered, including the opportunity for near continuous remote monitoring of at risk patients. Means to process and handle large volumes of information are needed, including neural networks, fuzzy logic, and expert systems. More effective education and training can be accomplished using the skills and techniques of the game and entertainment industry, particularly video, robotic, and virtual reality technologies.
John C. Wood, Andrew J. Buda, and Daniel T. Barry, "Time-Frequency Transforms: A New Approach to First Heart Sound Frequency Dynamics," IEEE Transactions on Biomedical Engineering, vol. 39, No. 7, pp. 730-740, July 1992. According to the authors the Binomial Transform provides much better resolution than the spectrograph or spectrogram, the two most common non-stationary signal analysis techniques. Previously, heart sound dynamic frequency analysis has primarily relied upon analog bandpass filtration methods such as the sound spectrograph. This method is time-consuming and requires expensive instrumentation. In addition, the overlapping filter passbands produce poor frequency resolution, particularly in the frequencies below 100 Hz.
Yasemin M. Akay, Metin Akay, Walter Welkowitz, John L. Semmlow and John B. Kostis, "Noninvasive Acoustical Detection of Coronary Artery Disease: A Comparative Study of Signal Processing Methods," Transactions on Biomedical Engineering, pp. 571-578, June 1993. The authors report that previous studies have indicated that heart sounds may contain information useful in the detection of occluded coronary arteries. In order to detect such sounds, recordings of diastolic heart sound segments were analyzed by using four signal processing techniques: the Fast Fourier Transform (FFT), the Autoregressive (AR), the Autoregressive Moving Average (ARMA), and the Minimum-Norm (Eigenvector) methods. To further enhance the diastolic heart sounds and reduce background noise, an Adaptive filter was used as a preprocessor. The results confirm that high-energy acoustic energy between 300 and 800 Hz is associated with coronary stenosis.
Yuan-Ting Zhang, Cyril Basil Frank, Rangaraj Mandayam Rangayyan and Gordon Douglas Bell, "A Comparative Study of Simultaneous Vibromyography with Active Human Quadriceps," IEEE Transactions on Biomedicel Engineering, vol. 39, No. 10, pp. 1045-1052, October 1992. Results of all these studies show that the VMG, as a direct mechanical index of muscular contraction, has potential as a noninvasive tool for studying the mechanical behavior of active skeletal muscles.
Arnon Cohen, "Signal Processing Methods for Upper Airway and Pulmonary Dysfunction Diagnosis," IEEE Engineering in Medicine and Biology Magazine, pp. 72-75, March 1990. According to this autor analysis of the acoustic characteristics of the thorax by sophisticated signal processing methods shows promise for assisting clinical diagnosis. The technique is simple, quantitative, non-invasive, and objective. In some cases, especially in pediatrics, it closes a gap between the simple stethoscope and expensive invasive methods. This inexpensive implementation will allow the development of home care systems for the analysis and long term monitoring of, for example, snoring or asthmatic attacks. The application of modern sophisticated signal processing methods to auscultation may overcome the disadvantages of conventional auscultation and provide a simple, inexpensive, non-invasive, objective, and quantitative diagnostic tool. Simple microphone transducers are used.
Ingvar Sodal and George Swanson, PH.D., "Making the mass spectrometer an efficient anesthetist's aide," EMB Magazine, March 1982. The authors have developed a quadrupole mass spectrometer that is a miniature device and has promising implications for anesthetic gas monitoring, critical patient care and for respiratory research. It could serve as a rapid, multichannel gas analyzer in the physiology laboratory. It should lead to the development of better noninvasive measurements of cardiac output and lung tissue volume.
Sateh M. Jalaleddine, Chriswell G. Hutchens, Robert D. Strattan and William A. Coberly, "ECG Data Compression Techniques--A Unified Approach," IEEE Transactions on Biomedical Engineering, vol. 37, No. 4, pp. 329-343, April 1990. The transformation methods, briefly presented, include: Fourier, Walsh, and K-L transforms. Data compression by the transformation or the direct data compression methods contains transformed or actual data from the original signal. Whereby, the original data are reconstructed by an inverse process. The objective . . . is to preserve the minimum essential information required to ensure reliable clinical diagnosis for a specific ECG lead(s) application. The result of this standardization . . . will include . . . improved quality of health care through a) more uniform, consistent, and proven methods, and b) elimination of proprietary solutions which are too often less than optimum, poorly substantiated, and costly.
James W. Waite, "A Multirate Bank of Digital Bandpass Filters for Acoustic Applications," Hewlett-Packard Journal, pp. 75-81, April 1993. Acousticians prefer to see the data distributed in constant percentage bandwidths, usually octave or 1/3 octave bands, since the auditory perception of sound is logarithmically related to frequency and several regulations require such presentation. The FFT has severe limitations for use in acoustics. The output of the FFT has a constant bandwidth distribution rather than a constant percentage bandwidth distribution, that is, the frequency scale is linear rather than logarithmic. The frequency of the lowest band is limited by a lack of resolution at the low-frequency end of the spectrum. An FFT analyzer that claims to match the performance of a traditional bank of analog 1/3-octave bandpass filters must overlap data acquisition and processing, and cannot disregard samples at its analog-to-digital converter at any time. Even in this world of faster processing horsepower, this is a difficult task given the considerations listed above. Filter analyzers are not without their own shortcomings. Constant percentage bandwidths allow only coarse frequency resolution toward the higher end of the acoustic spectrum, making the measurement of discrete tones difficult. Also, at low frequencies, the very narrowband 1/3-octave filters have long impulse responses, resulting in lengthy filter settling times. Wavelet analysis is a promising technology. Wavelets have properties that make them very attractive for the measurement of sound. For the immediate future, however, the world of sound is seen through the poles and zeros of bandpass filters, analog or digital. Digital Signal Processing (DSP) is also used by the acoustics community. Digital filters have for some time replaced the old analog 1/3-octave filter banks, and are available as dedicated real-time frequency analyzers or filter analyzers, as distinguished from FFT spectrum analyzers, dynamic signal analyzers, and others that derive their results from the FFT. The digital filter analyzers are typically composed of a subset of single-purpose filter gate arrays, bit-slice microprocessors, and medium-scale integration DSP multiplier-accumulators. Such dedicated hardware has made it difficult for the digital filter analyzers to perform other signal processing tasks.
What is needed is a new paradigm for the design of instruments for medical care, and, in particular, a new spectrum analyzer without the disadvantages associated with those now commercially available. This, then, is what the invention provides.